File size: 4,210 Bytes
803cb67 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | ---
id: task_035_comprehensive_decision_medium_medium010
name: comprehensive_decision-medium-medium010
category: comprehensive_decision
grading_type: llm_judge
timeout_seconds: 1200
gold_file: qa_gold/comprehensive_decision/medium010.json
workspace_files: [
{
"source": "database/bilingual_translation_english_chinese.json",
"dest": "database/bilingual_translation_english_chinese.json"
},
{
"source": "database/enterprise/company_core.csv",
"dest": "database/enterprise/company_core.csv"
},
{
"source": "database/enterprise/company_operation_status.csv",
"dest": "database/enterprise/company_operation_status.csv"
},
{
"source": "database/enterprise/company_operation_status_detail.csv",
"dest": "database/enterprise/company_operation_status_detail.csv"
},
{
"source": "database/enterprise/company_operation_yearly_status.csv",
"dest": "database/enterprise/company_operation_yearly_status.csv"
},
{
"source": "database/enterprise/company_profile.csv",
"dest": "database/enterprise/company_profile.csv"
},
{
"source": "database/enterprise/company_profile_as.csv",
"dest": "database/enterprise/company_profile_as.csv"
},
{
"source": "database/enterprise/company_profile_eu.csv",
"dest": "database/enterprise/company_profile_eu.csv"
},
{
"source": "database/enterprise/company_profile_na.csv",
"dest": "database/enterprise/company_profile_na.csv"
},
{
"source": "database/enterprise/company_profile_oc.csv",
"dest": "database/enterprise/company_profile_oc.csv"
},
{
"source": "database/industry/national_industry_status.csv",
"dest": "database/industry/national_industry_status.csv"
},
{
"source": "database/industry/national_industry_status_detail.csv",
"dest": "database/industry/national_industry_status_detail.csv"
},
{
"source": "database/industry/national_industry_yearly_status.csv",
"dest": "database/industry/national_industry_yearly_status.csv"
},
{
"source": "database/industry/regional_industry_status.csv",
"dest": "database/industry/regional_industry_status.csv"
},
{
"source": "database/industry/regional_industry_status_detail.csv",
"dest": "database/industry/regional_industry_status_detail.csv"
},
{
"source": "database/industry/regional_industry_yearly_status.csv",
"dest": "database/industry/regional_industry_yearly_status.csv"
},
{
"source": "database/internal_metrics.csv",
"dest": "database/internal_metrics.csv"
},
{
"source": "database/policy/policy_release_status.csv",
"dest": "database/policy/policy_release_status.csv"
},
{
"source": "database/policy/policy_resource.csv",
"dest": "database/policy/policy_resource.csv"
}
]
---
## Prompt
In 2022, in the provincial data for the construction industry, each province has an indicator reflecting the average asset-liability ratio (financial leverage level) of enterprises in that province's industry (considering only enterprises with valid total assets and total liabilities). Among the provinces covered by valid data, which province has the lowest value for this mean indicator, and what is that value?
Output guidelines:
The answer should be a numerical value (rounded to 2 decimal places), in units of %. If the relevant data cannot be found, please answer "No relevant data found"
Only use files under `./database/`.
## Expected Behavior
Agent should read the provided `database/` files, compute the result, and return the final answer. The final answer must follow the required output format.
## Grading Criteria
- [ ] Final answer semantically matches the gold `answer`.
- [ ] Output format follows `guidelines`.
## LLM Judge Rubric
### Criterion 1: Multi-answer Correctness (Weight: 100%)
Gold answer JSON:
`["Shanxi Province", 27.17]`
Scoring rules:
- The gold answer is a list with N=2 parts.
- Judge each predicted part against the corresponding gold part by semantic equivalence.
- Return `scores` with `part_0 ... part_1` each as 0 or 1.
- Return `total = (sum(part_i)) / 2` exactly.
- If the model output is missing or cannot be parsed into 2 comparable parts, score all parts 0.
|